Human exposure pathways to poly- and perfluoroalkyl substances (PFAS) from indoor media: A systematic review

Abstract

Human exposure to per- and polyfluoroalkyl substances (PFAS) has been primarily attributed to contaminated food and drinking water. However, PFAS exposure has also been linked to use of products. Few studies report relationships between these exposure media and human biomonitoring measurements. A systematic review (SR) is a transparent and rigorous method to evaluate a body of scientific evidence to answer a specific research or policy question. Although widely used in clinical medicine and epidemiology, the development of SR methods that are applicable to exposure science studies is ongoing. This study adapted SR methodologies to identify important PFAS exposure pathways from indoor environment media, including consumer products, household articles, cleaning products, personal care products, and indoor air and dust. Included studies present exposure measures from indoor media paired with occupant PFAS concentrations in blood serum, focusing specifically on perfluorooctanoic acid (PFOA) and perfluorooctanesulfonate (PFOS). Searches were conducted of Web of Science, PubMed, and ToxNet databases, where approximately 6,000 studies were identified. Machine learning approaches were used during the literature scoping and title/abstract screening to prioritize pathways by automated tagging and to select studies for inclusion using an iterative predictive screening model. Studies were screened against inclusion criteria by two independent reviewers. The extraction and summarization of study characteristics were performed in DistillerSR software, visualized in Tableau, and will be available for download. The exposure assessment methods used in included studies were evaluated using an approach modified from the EPA’s Systematic Review Protocol for IRIS Assessments and the Navigation Guide. This study presents innovative SR methodologies for exposure science studies, including the development of exposure pathway-specific search strings for use in artificial intelligence software. The evidence generated will increase our understanding of exposure to PFAS from indoor environment sources, identify key data gaps, and inform future research priorities.